:quality(75))
Customer and distribution
One relationship for every policyholder, not one policy at a time
Customer and distribution teams still see a policyholder through whichever product they last bought, and an agent or broker often knows less about the customer than the customer expects. Retention efforts start after someone has already decided to leave.
AI gives the relationship a fuller picture. Predictive models flag who's likely to leave and what they're ready to buy next. Generative AI drafts a personalized quote or bundle from the customer's full policy history. Agents handle routine service calls and summarize the ones that reach a person. Agents and brokers spend their time on the relationship, on infrastructure you control.
3 use cases
Agent and broker performance and next best actionPredictive models that score leads, compare producer performance, and suggest a next best action for each agent, broker or household, with reasons attached.Personalized product bundling for insurersMachine learning that predicts which additional policy or coverage each household is likely to need next, with a reason code, so agents, call centers and websites offer one relevant bundle instead of a generic package.Telematics-based insurance modelsMachine learning models that use vehicle driving data to score claims fraud, customer churn and billing risk for each policyholder, with reasons attached.
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